Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/2373
Title: A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
Authors: G. Wiman
Gustavo Schweickardt
Vladimiro Miranda
Issue Date: 2011
Abstract: Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.
URI: http://repositorio.inesctec.pt/handle/123456789/2373
metadata.dc.type: article
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